Virtualization-enabled dynamic functional split and resource mapping in optical data center networks [Invited]
The heterogeneity of applications and their divergent resource requirements lead to uneven traffic distribution and imbalanced resource utilization across data center networks (DCNs).We propose a fine-grained baseband function reallocation scheme in heterogeneous optical switching-based DCNs.A deep reinforcement learning-based functional split and resource mapping approach (DRL-BFM) is proposed to maximize throughput in high-load server racks by implementing load balancing in DCNs.The results demonstrate that DRL-BFM improves the throughput by 20.8%, 22.8%, and 29.8% on average compared to existing algorithms under different computational capacities, bandwidth constraints, and latency conditions, respectively.
Authors
- Bo Tian (ORCID: https://orcid.org/0009-0006-9890-659X)
- Lei Zhu (ORCID: https://orcid.org/0000-0001-9877-1337)
- Xiangjun Xin (ORCID: https://orcid.org/0009-0007-7075-3699)
- Qi Zhang (ORCID: https://orcid.org/0000-0003-3877-7758)
- Huan Chang (ORCID: https://orcid.org/0000-0002-8241-8763)
- Xiaolong Pan (ORCID: https://orcid.org/0000-0002-7835-1009)
- Shanting Hu (ORCID: https://orcid.org/0000-0002-2365-9057)
- Xiaofei Huang (ORCID: https://orcid.org/0009-0006-8611-8553)
Institutions
- Beijing Institute of Technology (CN)
- Beijing University of Posts and Telecommunications (CN)
- Beijing Electronic Science and Technology Institute (CN)
- System Equipment (China) (CN)
Publication Details
- Journal
- Chinese Optics Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.3788/col202523.050001
- Primary Topic
- Software-Defined Networks and 5G
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Beijing University of Posts and Telecommunications
- Beijing Institute of Technology
- Beijing Institute of Technology Research Fund Program for Young Scholars